LATIDIA · Investigación

Previsión de los riesgos meteorológicos espaciales en las redes eléctricas

Los fenómenos meteorológicos espaciales extremos pueden dañar los sistemas de energía en la Tierra y degradar la precisión del GPS y las operaciones de los satélites. Un nuevo sistema de aprendizaje automático puede predecir dónde es probable que se produzcan daños 30-60 minutos antes de una tormenta

La noticia

At a glance End-to-end forecasting: A machine learning pipeline uses forecast-time solar-wind information to generate location-specific risk estimates for 66,935 substations in the continental United States. Physics and place: The system combines Auroral Electrojet (AE) and Disturbance Storm Time (Dst) forecasts with local latitude, geology, and ground conductivity. Advance warning: The pipeline detected nearly 80% of major space-weather events during the evaluation period and can warn grid operators 30 to 60 minutes before a specific risk appears. Forecasting a threat to critical infrastructure During the May 2024 geomagnetic storm, utilities across North America prepared for possible impacts as auroras extended far beyond their usual range. The storm would degrade GPS